227 lines
7.0 KiB
Python
227 lines
7.0 KiB
Python
import os
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import re
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import yaml
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import logging
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from contextlib import asynccontextmanager
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from typing import Optional
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import json
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from fastapi import FastAPI, Query, HTTPException, Request
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from fastapi.middleware.cors import CORSMiddleware
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from version import __version__
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from ai_client import AIClient, QuestionInfo
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# ── 日志 ──────────────────────────────────────────────
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s [%(levelname)s] %(message)s",
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datefmt="%Y-%m-%d %H:%M:%S",
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)
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logger = logging.getLogger("ocs_ai")
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# ── 配置加载 ──────────────────────────────────────────
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def _resolve_env(value: str) -> str:
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"""解析 ${ENV_VAR} 格式的环境变量"""
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pattern = re.compile(r"\$\{([^}]+)\}")
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matches = pattern.findall(value)
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for var in matches:
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env_val = os.environ.get(var, "")
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value = value.replace(f"${{{var}}}", env_val)
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return value
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def load_config(path: str = "config.yaml") -> dict:
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with open(path, "r", encoding="utf-8") as f:
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config = yaml.safe_load(f)
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config["ai"]["api_key"] = _resolve_env(config["ai"]["api_key"])
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config["ai"]["api_base"] = _resolve_env(config["ai"]["api_base"])
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return config
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CONFIG = load_config()
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ai_client: Optional[AIClient] = None
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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global ai_client
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ai_cfg = CONFIG["ai"]
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ai_client = AIClient(
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api_key=ai_cfg["api_key"],
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api_base=ai_cfg["api_base"],
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model=ai_cfg["model"],
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vision_model=ai_cfg.get("vision_model", ""),
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temperature=ai_cfg.get("temperature", 0.1),
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max_tokens=ai_cfg.get("max_tokens", 500),
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timeout=ai_cfg.get("timeout", 60),
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thinking=ai_cfg.get("thinking", False),
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provider=ai_cfg.get("provider", "deepseek"),
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)
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logger.info(
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f"AI 客户端已初始化 | 文字模型: {ai_cfg['model']} | 视觉模型: {ai_cfg.get('vision_model') or '未配置'}"
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f" | 提供商: {ai_cfg.get('provider', 'deepseek')} | Thinking: {ai_cfg.get('thinking', False)}"
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)
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yield
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app = FastAPI(title="OCS × AI 中间件", version=__version__, lifespan=lifespan)
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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@app.head("/")
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@app.get("/")
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async def root():
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return {"status": "ok", "service": "OCS AI Middleware"}
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# ── 认证 ──────────────────────────────────────────────
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def verify_api_key(api_key: Optional[str]) -> None:
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"""验证服务端 API Key（如果配置了的话）"""
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required = CONFIG["server"].get("api_key", "")
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if required and api_key != required:
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raise HTTPException(status_code=403, detail="API Key 无效")
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# ── 接口 ──────────────────────────────────────────────
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def _sanitize_body(body: dict) -> dict:
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"""日志用：把 base64 图片、超长文本压缩掉，避免刷爆日志"""
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safe: dict = {}
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if not isinstance(body, dict):
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return {"_raw": str(body)[:200]}
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for key, value in body.items():
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if key == "images" and isinstance(value, list):
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safe[key] = f"<{len(value)} 张 base64 图片>"
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elif isinstance(value, str) and len(value) > 300:
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safe[key] = value[:300] + f"...(len={len(value)})"
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else:
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safe[key] = value
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return safe
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@app.get("/api/search")
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async def search_get(
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title: str = Query(..., description="题目标题"),
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type: str = Query(default="single", description="题目类型: single/multiple/judgement/completion"),
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options: str = Query(default="", description="题目选项，\\n 分隔"),
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api_key: Optional[str] = Query(default=None, description="服务端 API Key"),
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):
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"""GET 方式搜题 —— OCS 题库配置 method: get 时使用"""
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return await _do_search(title, type, options, api_key)
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@app.post("/api/search")
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async def search_post(request: Request):
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"""POST 方式搜题 —— OCS 题库配置 method: post 时使用（图片题优化需要 POST）"""
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try:
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body = await request.json()
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except Exception:
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body = {}
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if not isinstance(body, dict):
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body = {}
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if CONFIG["server"].get("log_requests", True):
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logger.info(
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f"POST 请求体: {json.dumps(_sanitize_body(body), ensure_ascii=False)}"
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)
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title = str(body.get("title", "") or "")
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qtype = str(body.get("type", "") or "") or "single"
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options = str(body.get("options", "") or "")
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api_key = body.get("api_key", None)
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# OCS 5.0 图片题优化字段
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images = body.get("images")
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if not isinstance(images, list):
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images = []
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suggestion_title = str(body.get("suggestion_title", "") or "")
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suggestion_options = str(body.get("suggestion_options", "") or "")
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return await _do_search(
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title,
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qtype,
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options,
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api_key,
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images=images,
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suggestion_title=suggestion_title,
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suggestion_options=suggestion_options,
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)
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ANSWER_SEPARATOR = "#"
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async def _do_search(
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title: str,
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qtype: str,
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options: str,
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api_key: Optional[str],
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images: Optional[list] = None,
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suggestion_title: str = "",
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suggestion_options: str = "",
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):
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verify_api_key(api_key)
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images = images or []
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if CONFIG["server"].get("log_requests", True):
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logger.info(
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f"收到题目 | 类型: {qtype} | 图片: {len(images)} 张 | "
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f"标题: {title[:80]}{'...' if len(title) > 80 else ''}"
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)
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question = QuestionInfo(
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title=title.strip(),
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type=qtype.strip(),
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options=options.strip(),
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images=images,
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suggestion_title=suggestion_title.strip(),
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suggestion_options=suggestion_options.strip(),
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)
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try:
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raw_answer = await ai_client.ask(question)
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if raw_answer is None or not raw_answer.strip():
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return {"code": 0, "msg": "AI 未返回有效答案"}
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answer = raw_answer.strip()
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logger.info(f"最终答案: {answer[:100]}")
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return {
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"code": 1,
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"question": title,
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"answer": answer,
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}
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except Exception as e:
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logger.error(f"AI 请求异常: {e}")
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return {"code": 0, "msg": str(e)}
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# ── 健康检查 ──────────────────────────────────────────
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@app.get("/health")
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async def health():
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return {"status": "ok", "model": CONFIG["ai"]["model"]}
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if __name__ == "__main__":
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import uvicorn
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svr = CONFIG["server"]
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logger.info(f"OCS × AI 中间件 v{__version__} → http://{svr['host']}:{svr['port']}")
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uvicorn.run(app, host=svr["host"], port=svr["port"])
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